I’m currently taking a research course. It’s the final formal course in my Master’s degree program, and after this, I will just have to do my thesis. In this research course, I have to design a study. I don’t have to do the study – I just have to design it. Which still involves tons of reading and hypothesizing and reviewing articles and writing. I’ve chosen to study complexity science and complex adaptive systems, and how the principles of complexity may be useful when applied either directly or metaphorically to software project development activities. This sounds spectacularly interesting to you, I’m sure.
Anyway, in order to figure out where I wanted to go with this stuff, I had to do a lot of reading on complexity to give myself a basis for the rest of the work. I had been introduced to the concept in an earlier course, but really didn’t know about it in any depth. One of the books I chose as a primer for myself is called Simply Complexity – a clear guide to complexity theory. After having read the book, I can say I support the author’s assertion that it is a clear guide to complexity theory. One of the reasons the author was successful was because he chose illustrations that were more entertaining than the core concepts alone would have been.
Quick background -you can think of agents as people, and a complex adaptive system as any group of people. An oversimplified way to explain complex adaptive systems is that they are open systems that consist of many agents that have some dependencies upon each other, interact together, can learn based on their own memory or other kinds of feedback, and therefore, they adapt over time, causing events to emerge at the whole system level, even without any kind of external controller telling them all what to do.
A typical example might be a traffic jam. Lots of people are trying to choose the best route to work, and they make their choices based on their memory of traffic patterns, and maybe a news report of what traffic looks like at the time they are leaving. They make their best guess, which can only be judged right or wrong based on what everyone else out on the road chooses to do. In that way, a traffic jam can form, consisting of a particular set of people, even though no single person coordinated the movements of all those people to get them to the places on the road at the exact times to create that particular traffic jam. The people that chose an alternative route were “right” in this case, though they couldn’t know they would be right until they got out on the road and drove to wherever they were going.
Fairly late in the book, the author attempts to explain how various types of mathematics and science can be used to explain the way agents in a complex adaptive system behave. He shares the results of a study that modeled human relationships and measured a virtual society’s dating habits to address the question of whether society is moving in a direction where there are fewer and fewer long-term relationships because individuals have become more and more picky about their mates over time. Virtual people were given lists of things they liked and disliked and a simulator had them wander around meeting others who they would pair up with based on how many elements of their lists were in common. The more they had in common, the longer they stayed together.
Each person in the population was labeled based on whether they were currently single or in a relationship and how many previous relationships they’d been in. Someone that was never in a relationship before and was still single was labeled 0S, and someone who was in a relationship and had two prior relationships was labeled 2R, and so on. It turns out that this labeling is what scientists studying nuclear physics do to describe radioactive decay. An atom starts out whole (0S), having never lost any part of itself to decay, then it decays a bit (0R), then stabilizes (1S), then decays (1R), then stabilizes (2S).
It is a little sobering to try to categorize yourself this way. If I count only serious relationships, then I am currently a 6R, but if I add in some of the questionable ones that didn’t last long, but still existed, I’d guess I’m more along the lines of a 10-12R. Measuring your own relationships, where do you sit on the scale of radioactive decay?